Behaviour and nesting ecology of Appalachian Ruffed Grouse (<em>Bonasa umbellus</em>)
Bibliographic record
Abstract
The substantial decline of Ruffed Grouse (Bonasa umbellus) in the southern Appalachian Mountains has been attributed in part to poor recruitment with possible links to nesting ecology. However, despite extensive research, the incubation ecology of Ruffed Grouse remains poorly understood. During 1999–2001 in West Virginia, we used videography of nesting female Ruffed Grouse to (1) quantify incubation constancy (minutes on the nest/minutes recorded) and nest survival during incubation, (2) determine whether incubation constancy predicts hatch success (proportion of eggs hatched per clutch), (3) determine the effect of the onset of laying on incubation constancy and hatch success, and (4) quantify nest visitors and depredation. Females spent about 96% of the recorded time incubating their clutches. Average incubation time per day increased by 1 h between day 1 and day 24 of incubation. Females generally left their nests twice daily, once in the morning between 0700 and 1000 for 31.7 ± 2.4 minutes (standard error) and again in the evening between 1600 and 1800 for 33.6 ± 1.5 minutes. Daily survival of nests (99.3 ± 0.4%) and nest survival for the incubation period (84.9 ± 9.3%) were high. Hatch success (the proportion of eggs that hatched among nests where at least one hatched) was high: 94.9 ± 0.02%. We found no relation between incubation constancy and hatch success. We recorded American Black Bear (Ursus americanus), Raccoon (Procyon lotor), and Long-tailed Weasel (Mustela frenata) as nest predators.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".